Enabled a document management firm to mine data accurately and improve operations efficiency through automation
Extracting Valuable Metadata AI-powered Text Analytics for Document Management
About the Client
The client is a world-leading contract and document management firm based in the US. Moreover, the client handles large volumes of contracts and documents for leading companies around the globe. Also, they help companies to retain and grow their base revenue with effective document management.
Business Challenge
We built an IT Operations Analytics tool that will give the client access to accurate dashboards, predictive pricing, and predictive analytics.
What Aptus Data Labs Did
We built an AI-based LDA (Latent Dirichlet Allocation) model to mine metadata efficiently.
The Impact Aptus Data Labs Made
The LDA model implemented for text analytics has effectively extracted valuable metadata, resulting in an 85% accuracy and a 6% improvement in operational efficiency.
The Business and Technology Approach
Aptus Data Labs used the below process to build the text analytics model to resolve the existing challenge.
Used text filtration to extract data based on titles, dates, contract party details, document category, and contact details
Used the following application to retrieve useful data:
- Entity Extraction
- Name Matching
- Stop Word Removal
- Stemming
- Tokenization
- Categorization
- Topic Extraction
- Transformation of Cases
- Words to Vector
- Sentence Extraction
- Naïve Bayes Classification
Tools used
- RapidMiner
- ‘R’ Code integrated into Rapid Miner
The Outcome
The derived data helped the client to automate their process and increased their operations efficiency by 6%.
If you’re looking to take your business to the next level with data science, we invite you to contact us today to schedule a consultation. Our team will work with you to assess your current data landscape and develop a customized solution that will help you gain valuable insights and drive growth.